Project Summary/ Abstract Despite nearly one million births involving labor induction annually in the United States, substantial variability in the protocols and interventions used for induction exists among providers. Induced labors are longer and require more hospital resources than spontaneous labors. Moreover, the approach, route, and dose involved in labor induction may result in adverse clinical outcomes or patient experience of labor. Therefore, it is imperative to determine optimal methods of labor induction that minimize harm and maximize benefits while balancing operational costs. In this K01 application, we propose to utilize advanced statistical techniques to study interventions and timing of labor induction, focusing on benefits, risks, patient preferences, and resource use. This project will benefit from multiple data sources at Women & Infants Hospital including the labor, delivery, and recovery floor delivery log, labor induction intake forms, pharmacy claims, patient charts, the electronic medical record system, and hospital discharge data. Aim 1 will establish what is known about the comparative effectiveness of labor induction through a systematic review and meta-analysis. Within the clinical setting at Women & Infants Hospital, we will establish a comprehensive database of deliveries involving labor induction which will be supplemented by a questionnaire administered to postpartum patients about their labor induction experience. Analyses conducted as part of Aim 2 will explore patient-centered outcomes and will apply existing knowledge to the Women & Infants data using mathematical modeling to integrate interventions for labor induction with different types of outcomes and analyzing treatment effect heterogeneity. The methodological approach for Aim 3 will include decision analyses and value of information analyses to identify the most critical areas for future research in other populations. Throughout the project, we will engage stakeholders that have interest in labor induction including patients, physicians, hospital operations committee, insurance providers, health departments, and policy makers. The contribution of the proposed research is in better synthesizing existing studies as well as conducting a prospective analysis that incorporates multiple interventions and balances multiple outcomes. In every aim of this application, we propose innovative approaches that will shift current research standards and subsequently influence clinical practice norms. These technologies and methods are not often used in combination in a continuum of the same study and are not widely used in obstetrics. The results of the meta-analysis in Aim 1 will lead to a comprehensive summary of labor induction practices and outcomes studied to-date. We will then use these results to help inform the analyses in Aim 2. The findings from the mathematical modeling in Aim 2 have the potential to influence policy and obstetric practice recommendations. The results from the value of information analysis in Aim 3 will help prioritize the future research agenda in labor induction. We will use the findings of our analyses to translate results into practice and inform future research needs.